I have a collection containing documents. Each document has a part attribute containing an Array of Hash (documents). These documents may or may not have a _encwas attribute.
{
_id : "00001",
parts : [
{ _encwas: 1, body: "" },
{ body: "" }
]
},
{
_id : "00002",
parts : [
{ _encwas: 1, body: "" },
{ _encwas: 2, body: "" }
]
},
{
_id : "00003",
parts : [
{ body: "" },
{ body: "" }
]
}
Is there a quick way to find all records where at least one part contains a _encwas attribute?
The following query works
db.collection.find({ "parts.0._encwas" : { $exists : true } });
but I would love to find a way to replace 0 with any part. For example
db.collection.find({ "parts.*._encwas" : { $exists : true } });
The query should be as efficient as possible (I don't mind if I need to create additional indexes) because I need to iterate more than 1M records.
This seemed to work when I tried with your test data:
db.collection.find( { "parts._encwas": { $exists : true } } )
Moreover, you can find all documents containing _encwas having a specific value using:
db.collection.find( { "parts._encwas": 4 } )
...where 4 is the value...
I believe the relevant part of the documentation is here: Dot Notation
Related
I have a JSON in MongoDB and I am trying to check if at least one of the items in the JSON doesn't contain a specific field.
{
"_id" : 12345,
"orderItems" : [
{
"itemId" : 45678,
"isAvailable" : true,
"isEligible" " false
},
{
"itemId" : 87653,
"isAvailable" : true
}
]
}
So in the above JSON, since the 2nd one under order items doesn't contain iseligible field, I need to get this _id.
I tried the below query so far, which didnt work:
db.getCollection('orders').find({"orderItems.iseligible":{$exists:false})
You can use $elemMatch to evaluate the presence of the nested key. Once that's accomplished, project out the _id value.
db.orders.find({
orderItems: {
$elemMatch: {
"isEligible": {
$exists: false
}
}
}
},
{
_id: 1
})
Here is a Mongo playground with the finished code, and a similar SO answer.
I have a document like this:
{
"_id" : "4mDYgt6gID",
...
"MultipleChoiceQuestions" : [
{
...
"LeadInFile" : null,
...
},
{
...
"LeadInFile" : 'some string',
...
}
],
...
}
How do I query for any documents that have a non-null value in LeadInFile?
I'm trying different things, currently something like this
db.getCollection('QuizTime:Quizzes').find({"MultipleChoiceQuestions": [{ "LeadInFile": { $ne: null}}]});
Is returning 0 records.
The current form of the query is saying:
Find documents where MultipleChoiceQuestions is [{ "LeadInFile": { $ne: null}}]
Try using dot notation; this is used to access elements of an array or fields in an embedded document. For example:
db.getCollection('QuizTime:Quizzes').find({
"MultipleChoiceQuestions.LeadinFile" : { "$ne" : null }
})
I have a tricky mongoDB problem that I have never encountered.
The Documents:
The documents in my collection have a search object containing named keys and array values. The keys are named after one of eight categorys and the corresponding value is an array containing items from that category.
{
_id: "bRtjhGNQ3eNqTiKWa",
/* */
search :{
usage: ["accounting"],
test: ["knowledgetest", "feedback"]
},
test: {
type:"list",
vals: [
{name:'knowledgetest', showName: 'Wissenstest'},
{name:'feedback', showName: '360 Feedback'},
]
},
usage: {
type:"list",
vals: [
{name:'accounting', showName: 'Accounting'},
]
}
},
{
_id: "7bgvegeKZNXkKzuXs",
/* */
search :{
usage: ["recruiting"],
test: ["intelligence", "feedback"]
},
test: {
type:"list",
vals: [
{name:'intelligence', showName: 'Intelligenztest'},
{name:'feedback', showName: '360 Feedback'},
]
},
usage: {
type:"list",
vals: [
{name:'recruiting', showName: 'Recruiting'},
]
}
},
The Query
The query is an object containing the same category - keys and array - values.
{
usage: ["accounting", "assessment"],
test : ["feedback"]
}
The desired outcome
If the query is empty, I want all documents.
If the query has one category and any number of items, I want all the documents that have all of the items in the specified category.
If the query has more then one category, I want all the documents that have all of the items in all of the specified categorys.
My tries
I tried all kinds of variations of:
XX.find({
'search': {
"$elemMatch": {
'tool': {
"$in" : ['feedback']
}
}
}
No success.
EDIT
Tried: 'search.test': {$all: (query.test ? query.test : [])} which gives me no results if I have nothing selected; the right documents when I am only looking inside the test category; and nothing when I additionally look inside the usage category.
This is at the heart of my app, thus I historically put up a bounty.
let tools = []
const search = {}
for (var q in query) {
if (query.hasOwnProperty(q)) {
if (query[q]) {
search['search.'+q] = {$all: query[q] }
}
}
}
if (Object.keys(query).length > 0) {
tools = ToolsCollection.find(search).fetch()
} else {
tools = ToolsCollection.find({}).fetch()
}
Works like a charm
What I already hinted at in the comment: your document structure does not support efficient and simple searching. I can only guess the reason, but I suspect that you stick to some relational ideas like "schemas" or "normalization" which just don't make sense for a document database.
Without digging deeper into the problem of modeling, I could imagine something like this for your case:
{
_id: "bRtjhGNQ3eNqTiKWa",
/* */
search :{
usage: ["accounting"],
test: ["knowledgetest", "feedback"]
},
test: {
"knowledgetest" : {
"showName": "Wissenstest"
},
"feedback" : {
"showName": "360 Feedback"
}
},
usage: {
"accounting" : {
"values" : [ "knowledgetest", "feedback" ],
"showName" : "Accounting"
}
}
},
{
_id: "7bgvegeKZNXkKzuXs",
/* */
search : {
usage: ["recruiting"],
test: ["intelligence", "feedback"]
},
test: {
"intelligence" : {
showName: 'Intelligenztest'
},
"feedback" : {
showName: '360 Feedback'
}
},
usage: {
"recruiting" : {
"values" : [ "intelligence", "feedback" ],
"showName" : "Recruiting"
}
}
}
Then, a search for "knowledgetest" and "feedback" in "accounting" would be a simple
{ "usage.accounting.values" : { $all : [ "knowledgetest", "feedback"] } }
which can easily be used multiple times in an and condition:
{
{ "usage.accounting.values" : { $all : [ "knowledgetest", "feedback"] } },
{ "usage.anothercategory.values" : { $all [ "knowledgetest", "assessment" ] } }
}
Even the zero-times-case matches your search requirements, because an and-filter with none of these criteria yields {} which is the find-everything filter expression.
Once more, to make it absolutely clear: when using mongo, forget everything you know as "best practice" from the relational world. What you need to consider is: what are your queries, and how can my document model support these queries in an ideal way.
I have a user model like this:
user : {
myArmy : {
mySoldiers : [
{
positioned : false,
soldierInfo : {
_id : s99212
}
},
{
positioned : true,
soldierInfo : {
_id : s99112
}
}
]
}
},
user : {
myArmy : {
mySoldiers : [
{
positioned : true,
soldierInfo : {
_id : s99212
}
},
{
positioned : false,
soldierInfo : {
_id : s99112
}
}
]
}
}
...
I have a query that i want to do to return the user(s) who have soldier id s99212 positioned (true): (could be thousands of those, and i need to read and retrieve them all)
This is my faulty query with mongoose:
var soldierId = s99212;
stream = User.find({
$and: [
{'myArmy.mySoldier.positioned': {$ne: null}},
{'myArmy.mySoldier.soldierInfo._id': soldierId}
]
}).lean(true).stream();
Nothing is returned by this query, should there be another way to do this $and stuff?
How exactly am i suppose to use $elemMatch if at all, should it be instead of the find? (If it worth to mention, i want to return the complete user object, not just parts of it...)
Tried this, crashed my app:
stream = User.find({
'$elemMatch': [
{'myArmy.mySoldiers.pos': {$ne: null}},
{'myArmy.mySoldiers.soldierInfo._id': soldierId}
]
}).lean(true).stream();
I know i have a small syntax problem, where is it?
Very simple and well documented. The $elemMatch operator acts as a "query in itself", where it applies "it's conditions" to members of the array specified:
var query = User.find({
"myArmy.mySoldiers": {
"$elemMatch": {
"positioned": { "$ne": null },
"soldierInfo._id": soldierId
}
}
});
Therefore for a document to "match" then the conditions specfied under $elemMatch must be present and valid for the "same" array element. Array on "left", arguments on "right".
Other "dot notation" forms only ever test that the values match "some element" in the array, and not necessarily the same one.
Is there a way to conditionally $addToSet based on a specific key field in a subdocument on an array?
Here's an example of what I mean - given the collection produced by the following sample bootstrap;
cls
db.so.remove();
db.so.insert({
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples"
}
]
});
n defines a unique document key. I only want one entry with the same n value in the array at any one time. So I want to be able to update the pfms array using n so that I end up with just this;
{
"Name": "fruitBowl",
"pfms" : [
{
"n" : "apples",
"mState": 1111234
}
]
}
Here's where I am at the moment;
db.so.update({
"Name": "fruitBowl",
},{
// not allowed to do this of course
// "$pull": {
// "pfms": { n: "apples" },
// },
"$addToSet": {
"pfms": {
"$each": [
{
"n": "apples",
"mState": 1111234
}
]
}
}
}
)
Unfortunately, this adds another array element;
db.so.find().toArray();
[
{
"Name" : "fruitBowl",
"_id" : ObjectId("53ecfef5baca2b1079b0f97c"),
"pfms" : [
{
"n" : "apples"
},
{
"n" : "apples",
"mState" : 1111234
}
]
}
]
I need to effectively upsert the apples document matching on n as the unique identifier and just set mState whether or not an entry already exists. It's a shame I can't do a $pull and $addToSet in the same document (I tried).
What I really need here is dictionary semantics, but that's not an option right now, nor is breaking out the document - can anyone come up with another way?
FWIW - the existing format is a result of language/driver serialization, I didn't choose it exactly.
further
I've gotten a little further in the case where I know the array element already exists I can do this;
db.so.update({
"Name": "fruitBowl",
"pfms.n": "apples",
},{
$set: {
"pfms.$.mState": 1111234,
},
}
)
But of course that only works;
for a single array element
as long as I know it exists
The first limitation isn't a disaster, but if I can't effectively upsert or combine $addToSet with the previous $set (which of course I can't) then it the only workarounds I can think of for now mean two DB round-trips.
The $addToSet operator of course requires that the "whole" document being "added to the set" is in fact unique, so you cannot change "part" of the document or otherwise consider it to be a "partial match".
You stumbled on to your best approach using $pull to remove any element with the "key" field that would result in "duplicates", but of course you cannot modify the same path in different update operators like that.
So the closest thing you will get is issuing separate operations but also doing that with the "Bulk Operations API" which is introduced with MongoDB 2.6. This allows both to be sent to the server at the same time for the closest thing to a "contiguous" operations list you will get:
var bulk = db.so.initializeOrderedBulkOp();
bulk.find({ "Name": "fruitBowl", "pfms.n": "apples": }).updateOne({
"$pull": { "pfms": { "n": "apples" } }
});
bulk.find({ "Name": "fruitBowl" }).updateOne({
"$push": { "pfms": { "n": "apples", "state": 1111234 } }
})
bulk.execute();
That pretty much is your best approach if it is not possible or practical to move the elements to another collection and rely on "upserts" and $set in order to have the same functionality but on a collection rather than array.
I have faced the exact same scenario. I was inserting and removing likes from a post.
What I did is, using mongoose findOneAndUpdate function (which is similar to update or findAndModify function in mongodb).
The key concept is
Insert when the field is not present
Delete when the field is present
The insert is
findOneAndUpdate({ _id: theId, 'likes.userId': { $ne: theUserId }},
{ $push: { likes: { userId: theUserId, createdAt: new Date() }}},
{ 'new': true }, function(err, post) { // do the needful });
The delete is
findOneAndUpdate({ _id: theId, 'likes.userId': theUserId},
{ $pull: { likes: { userId: theUserId }}},
{ 'new': true }, function(err, post) { // do the needful });
This makes the whole operation atomic and there are no duplicates with respect to the userId field.
I hope this helpes. If you have any query, feel free to ask.
As far as I know MongoDB now (from v 4.2) allows to use aggregation pipelines for updates.
More or less elegant way to make it work (according to the question) looks like the following:
db.runCommand({
update: "your-collection-name",
updates: [
{
q: {},
u: {
$set: {
"pfms.$[elem]": {
"n":"apples",
"mState": NumberInt(1111234)
}
}
},
arrayFilters: [
{
"elem.n": {
$eq: "apples"
}
}
],
multi: true
}
]
})
In my scenario, The data need to be init when not existed, and update the field If existed, and the data will not be deleted. If the datas have these states, you might want to try the following method.
// Mongoose, but mostly same as mongodb
// Update the tag to user, If there existed one.
const user = await UserModel.findOneAndUpdate(
{
user: userId,
'tags.name': tag_name,
},
{
$set: {
'tags.$.description': tag_description,
},
}
)
.lean()
.exec();
// Add a default tag to user
if (user == null) {
await UserModel.findOneAndUpdate(
{
user: userId,
},
{
$push: {
tags: new Tag({
name: tag_name,
description: tag_description,
}),
},
}
);
}
This is the most clean and fast method in the scenario.
As a business analyst , I had the same problem and hopefully I have a solution to this after hours of investigation.
// The customer document:
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK"
}
]
}
// The problem : I want to insert dateField "01.01.2016" to customer documents where customerCodes subdocument has a document with code "YK" but does not have dateField. The final document must be as follows :
{
"id" : "1212",
"customerCodes" : [
{
"code" : "I"
},
{
"code" : "YK" ,
"dateField" : "01.01.2016"
}
]
}
// The solution : the solution code is in three steps :
// PART 1 - Find the customers with customerCodes "YK" but without dateField
// PART 2 - Find the index of the subdocument with "YK" in customerCodes list.
// PART 3 - Insert the value into the document
// Here is the code
// PART 1
var myCursor = db.customers.find({ customerCodes:{$elemMatch:{code:"YK", dateField:{ $exists:false} }}});
// PART 2
myCursor.forEach(function(customer){
if(customer.customerCodes != null )
{
var size = customer.customerCodes.length;
if( size > 0 )
{
var iFoundTheIndexOfSubDocument= -1;
var index = 0;
customer.customerCodes.forEach( function(clazz)
{
if( clazz.code == "YK" && clazz.changeDate == null )
{
iFoundTheIndexOfSubDocument = index;
}
index++;
})
// PART 3
// What happens here is : If i found the indice of the
// "YK" subdocument, I create "updates" document which
// corresponds to the new data to be inserted`
//
if( iFoundTheIndexOfSubDocument != -1 )
{
var toSet = "customerCodes."+ iFoundTheIndexOfSubDocument +".dateField";
var updates = {};
updates[toSet] = "01.01.2016";
db.customers.update({ "id" : customer.id } , { $set: updates });
// This statement is actually interpreted like this :
// db.customers.update({ "id" : "1212" } ,{ $set: customerCodes.0.dateField : "01.01.2016" });
}
}
}
});
Have a nice day !